## What changes were proposed in this pull request?
Currently JDBC data source creates tables in the target database using the default type mapping, and the JDBC dialect mechanism. If users want to specify different database data type for only some of columns, there is no option available. In scenarios where default mapping does not work, users are forced to create tables on the target database before writing. This workaround is probably not acceptable from a usability point of view. This PR is to provide a user-defined type mapping for specific columns.
The solution is to allow users to specify database column data type for the create table as JDBC datasource option(createTableColumnTypes) on write. Data type information can be specified in the same format as table schema DDL format (e.g: `name CHAR(64), comments VARCHAR(1024)`).
All supported target database types can not be specified , the data types has to be valid spark sql data types also. For example user can not specify target database CLOB data type. This will be supported in the follow-up PR.
Example:
```Scala
df.write
.option("createTableColumnTypes", "name CHAR(64), comments VARCHAR(1024)")
.jdbc(url, "TEST.DBCOLTYPETEST", properties)
```
## How was this patch tested?
Added new test cases to the JDBCWriteSuite
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#16209 from sureshthalamati/jdbc_custom_dbtype_option_json-spark-10849.
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